1. Technical Field
The present invention relates generally to manufacturing and other organizational activities in which a multiplicity of tasks are simultaneously balanced against one another to achieve goals of the organization. More specifically, the present invention relates to a system for allocating resources to lots to optimize organizational efficiency.
2. Background Art
A manufacturer who applies a variety of resources to produce a variety of products must make judgments concerning a "best" allocation of resources to products. A best allocation is evaluated in light of the manufacturer's goals. For example, one product lot may be given priority over other product lots because it has a tight schedule or it may be behind in its schedule. Thus, such a high priority lot is favored in allocating resources. Alternatively, a manufacturer may wish to utilize one resource as efficiently as possible to minimize costs. Labor or an exceptionally expensive piece of equipment may be allocated to product lots in a manner which causes these resources to stay busy at a maximum capacity. Judgments must occur to balance one lot's demand for resources against another lot's demand, to balance a desire to expedite a lot against the desire to efficiently use certain resources, and to balance any single lot's demands for resources against overall organizational goals. In a complex organization with a multiplicity of diverse lots contending for a multiplicity of diverse resources, exceedingly complex potential allocation scenarios result, and such "best" judgments are difficult to achieve.
In a typical organization, allocation of resources to lots occurs in two "arenas." The first arena is that of "virtual" allocations. Virtual allocations are the result of using planning and scheduling tools and techniques. Critical Path Method (CPM), Project Evaluation and Review Technique (PERT), and Material Requirements Planning (MRP) represent a few of the conventional planning techniques. In a virtual allocation, no resources are actually used or managed in connection with processing a lot. Rather, information is organized and recorded to describe an intention, plan, or schedule to use various resources in connection with the processing of various lots. Typically, these virtual allocations describe future anticipated activities of the organization.
In contrast to virtual allocations, organizations also perform "actual" allocations of resources to lots. Actual allocations occur when an organization uses resources in connection with the processing of real lots. Of necessity, actual allocations relate to present and past activities of the organization. While virtual allocations are merely informational tasks, actual allocations result from ongoing organizational activities. In addition, an actual allocation may correspond to an informational task which records or otherwise describes actual allocations.
At best, an organization might expect or hope that its actual allocations will mimic its conventionally achieved virtual allocations. However, prior art manufacturing and planning systems fall far short of being able to suggest an optimal virtual allocation of product demands with resources. Consequently, actually achieving an optimal allocation is nearly impossible using conventional techniques.
One explanation for the problems of prior art systems is that virtual allocations generated by such systems are often unrealistic. For example, such conventional systems typically generate virtual allocations based on an assumption that all resources, whether labor or equipment, are treated the same when they are actually allocated. In reality, manufacturers often treat different resources differently. Thus, plans made using such conventional systems are flawed from the outset, and actual allocations tend to differ markedly from the virtual allocations.
In addition, prior art systems often use simplistic "hard" prioritization schemes in allocating resources to lots. Such hard prioritization schemes allocate a resource first to a lot having a higher priority then allocate the resource to a lower priority lot. This and other prioritization schemes often lead to an inefficient use of resources in a complex allocation scenario. In a complex allocation scenario, an allocation of a resource to a lot may often be delayed without harming the lot's overall completion time because of downstream bottlenecks in the lot's processing flow. In such situations, lower priority lots may utilize a resource before the higher priority lots without harming the higher priority lots' completion time. Conventional planning systems which fail to allow lower priority lots to receive resources ahead of higher priority lots in such situations inefficiently allocate resources.
Moreover, such conventional systems typically operate by traversing backward in time. In other words, a desired output time, or deadline, for a product lot is supplied to the system, and the system works backward in time from this deadline to determine when various processes need to be started and completed in order to meet the deadline. Unrealistic plans often result because the system focuses on processes needed to accomplish deadlines more than on resources practically available for allocation or on whether a desired deadline is realistic. Consequently, such virtual allocations are expected to describe only that which an organization believes must happen in order to meet a deadline and not that which can or will actually happen.
Of course, an actual manufacturing environment does not operate backwards through time. Thus, a consequence of such backward traversal is that the prior art systems fail to adequately simulate actual operation of manufacturing environments. For example, prior art systems do not automatically evaluate alternate resource allocation outcomes in generating plans. As a result, the generation of an efficient plan using conventional planning systems is a hit-or-miss proposition at best.
On the other hand, an organization would receive substantial benefits if it could make virtual allocations that could be closely mimicked by actual allocations. Specifically, such mimicry would permit optimized organizational efficiency. Accurate virtual allocation would permit improved use of resources. For example, resources could be kept busy at optimal efficiencies for longer periods of time. Additionally, lots could be sized, designed, and otherwise managed for improved processing, given an organization's resources. Moreover, with close mimicry of actual allocations to virtual allocations, an organization could improve predictions for when its lots would be completed.